Purpose: This project will develop simple predictive model systems for microbial heat resistance for pathogenic strains of Salmonella by determining the thermal resistances of Salmonella serovars in moist, intermediate, and low-water activity environments.
Methods: Salmonella (n = 10) associated with low-moisture foods were grown on tryptic soy agar with yeast extract, harvested via physical removal, and inoculated into buffered peptone water (BPW), corn syrup, peanut butter and flour. Samples (80µL) were individually heated at a prescribed rate (5°C/min) to 55-90°C in a differential scanning calorimeter. Surviving Salmonella was enumerated via plate count. D- and z-values were calculated by plotting log (log N0/N) versus temperature. The inverse slope of the line is the z-value. The D-value at a desired temperature is determined by the y-intercept at that temperature
Results: As water activity decreased there was a significant increase in D-values for all Salmonella tested (P < 0.05). While all Salmonella investigated were more resistant in corn syrup (D70°C = 2.15-156 min) than BPW (D70°C = 0.01-0.18 min), the thermal resistance of the serovars did not follow the same resistance trend. In BPW S. Tennessee and S. Agona exhibited the greatest thermal resistance, with a D70°C = 0.18 min. In corn syrup S. Typhimurium and S. Anatum were the most thermally resistant, D70°C = 52.6 and 156 min, respectively.
Significance: As Salmonella serovars exhibit different thermal death kinetics depending on matrix, development of these predictive models will be essential for establishing preventive controls for these pathogens in low-moisture foods.